Agentic Framework is a versatile, open-source framework designed to streamline the creation of autonomous AI agents that leverage large language models and MongoDB. It equips developers with modular components for managing agent memory, defining toolsets, orchestrating multi-step workflows, and templating prompts. The integrated MongoDB-backed memory store enables agents to maintain persistent context across sessions, while pluggable tool interfaces allow seamless interaction with external APIs and data sources. Built on Node.js, the framework includes logging, monitoring hooks, and deployment examples to rapidly prototype and scale intelligent agents. With customizable configuration, developers can tailor agents for tasks such as knowledge retrieval, automated customer support, data analysis, and process automation, reducing development overhead and accelerating time-to-production.

Autonomous Agents is an open-source Python library designed to simplify the creation of autonomous AI agents powered by large language models. By abstracting core components such as perception, reasoning, and action, it allows developers to define custom tools, memories, and strategies. Agents can autonomously plan multi-step tasks, query external APIs, process results through custom parsers, and maintain conversational context. The framework supports dynamic tool selection, sequential and parallel task execution, and memory persistence, enabling robust automation for tasks ranging from data analysis and research to email summarization and web scraping. Its extensible design facilitates easy integration with different LLM providers and custom modules.

Chatchat Lite is an open-source, lightweight chat UI framework designed to run in the browser and connect to multiple AI backends—including OpenAI, Azure, custom HTTP endpoints, and local language models. It provides real-time streaming responses, Markdown rendering, code block formatting, theme toggles, and persistent conversation history. Developers can extend it with custom plugins, environment-based configurations, and adaptability for self-hosted or third-party AI services, making it ideal for prototypes, demos, and production chat apps.

Eliza is a lightweight, open-source conversational framework that simulates a psychotherapist via pattern matching and scripted templates. Developers can define custom scripts, patterns, and memory variables to tailor responses and conversation flows. It runs in any modern browser or webview environment, supports multiple sessions, and logs interactions for analysis. Its extensible architecture allows integration into web pages, mobile apps, or desktop wrappers, making it a versatile tool for education, research, prototype development, and interactive installations.

multiagent-golang provides a structured approach to building multi-agent systems in Go. It introduces an Agent abstraction where each agent can be equipped with various sensors to perceive its environment and actuators to take actions. Agents run concurrently using Go routines and communicate through dedicated messaging channels. The framework also includes an environment simulation layer to handle events, manage the agent lifecycle, and track state changes. Developers can easily extend or customize agent behaviors, configure simulation parameters, and integrate additional modules for logging or analytics. It streamlines the creation of scalable, concurrent simulations for research and prototyping.

SPEAR (Scalable Platform for Edge AI Real-Time) is designed to manage the full lifecycle of AI inference at the edge. Developers can define streaming pipelines that ingest sensor data, videos, or logs via connectors to Kafka, MQTT, or HTTP sources. SPEAR dynamically deploys containerized models to worker nodes, balancing loads across clusters while ensuring low-latency responses. It includes built-in model versioning, health checks, and telemetry, exposing metrics to Prometheus and Grafana. Users can apply custom transformations or alerts through a modular plugin architecture. With automated scaling and fault recovery, SPEAR delivers reliable real-time analytics for IoT, industrial automation, smart cities, and autonomous systems in heterogeneous environments.

Joylive Agent offers a modular, plugin-based architecture tailored for building sophisticated AI agents. It provides seamless integration with LLMs such as OpenAI GPT, configurable memory backends for session persistence, and a toolkit manager to expose external APIs or custom functions as agent capabilities. The framework also includes built-in chain-of-thought orchestration, multi-turn dialogue management, and a RESTful server for easy deployment. Its Java core ensures enterprise-grade stability, allowing teams to rapidly prototype, extend, and scale intelligent assistants across various use cases.